---
title: PDF Password Reader
---

The **PDF Password Reader** handles password-protected PDF files, allowing you to process secure documents and convert them into searchable knowledge bases.

## Code

```python examples/concepts/knowledge/readers/pdf_reader_password.py
from agno.agent import Agent
from agno.knowledge.content import ContentAuth
from agno.knowledge.knowledge import Knowledge
from agno.utils.media import download_file
from agno.vectordb.pgvector import PgVector

db_url = "postgresql+psycopg://ai:ai@localhost:5532/ai"
download_file(
    "https://agno-public.s3.us-east-1.amazonaws.com/recipes/ThaiRecipes_protected.pdf",
    "ThaiRecipes_protected.pdf",
)

# Create a knowledge base with simplified password handling
knowledge = Knowledge(
    vector_db=PgVector(
        table_name="pdf_documents_password",
        db_url=db_url,
    ),
)

knowledge.add_content(
    path="ThaiRecipes_protected.pdf",
    auth=ContentAuth(password="ThaiRecipes"),
)

# Create an agent with the knowledge base
agent = Agent(
    knowledge=knowledge,
    search_knowledge=True,
)

agent.print_response("Give me the recipe for pad thai")
```

## Usage

<Steps>
  <Snippet file="create-venv-step.mdx" />

  <Step title="Install libraries">
    ```bash
    pip install -U pypdf sqlalchemy psycopg pgvector agno openai
    ```
  </Step>
 
  <Step title="Set environment variables">
    ```bash
    export OPENAI_API_KEY=xxx
    ```
  </Step>

  <Snippet file="run-pgvector-step.mdx" />

  <Step title="Run Agent">
    <CodeGroup>
    ```bash Mac
    python examples/concepts/knowledge/readers/pdf_reader_password.py
    ```

    ```bash Windows
    python examples/concepts/knowledge/readers/pdf_reader_password.py
    ```
    </CodeGroup>
  </Step>
</Steps>

## Params

<Snippet file="pdf-reader-reference.mdx" />